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Tadesse Kebede
Data Engineer
Addis Ababa, Ethiopia
Haramaya University (2019-2020)
MSc. (Computer Science)
MSc. (Computer Science)
Mekelle University (2012-2016)
BSc. (Computer Science)
BSc. (Computer Science)
Email: taddeekb@gmail.com
Linkden: Tadesse Kebede | LinkedIn
Programming Languages
Programming Languages
Python,JavaScript, Java, SQL, C#
Data Analysis
Data Analysis
Pandas, Numpy, Matplotlib, Seaborn,Plotly
Machine Learning
Machine Learning
Scikit-learn, TensorFlow, Keras, MLflow, EDA, NLP, Computer Vision
DevOps & MLOps
DevOps & MLOps
CI/CD, Docker, Git Kubernetes, CML, DVC, unit testing
Data Engineering
Data Engineering
Kafka, Spark, Airflow, dbt, MySQL, AWS
Kafka, Spark, Airflow, dbt, MySQL, AWS
Web development & Visualization Tools
Web development & Visualization Tools
HTML, CSS, React, Streamlit, Python Flask, Heroku, Excel
About me
I am a Junior Data Engineer with a background in Computer Science. I am proficient in OOP programming, SQL, Python, and Bash. I am experienced in ETL, data pre-processing, visualization, data & analytics engineering, Machine Learning, Deep Learning, and developing an end-to-end data pipeline using Kafka, Airflow and Spark. I am also a good team player with excellent communication, writing and research skills.
Education
- Machine Learning, Data and Web3 Engineering • 9 May to 27 July 2022• 10Academy
Done different hands on Machine learning, Deep learning, Data Engineering and Web3
projects both individually and in a group.
Currently I have Certified "Machine Learning Engineering, Data Engineering and Web3 Engineering ", endorsed by 10 Academy. On the training I have worked on individual projects and with teams on solving real-world problems as summarized in the portfolio listing. Some of the responsibilities performed were; data extraction, data cleaning, prediction using machine learning, developing web3Dapps, writing reports, and visualizations.
- BA in Management• October 27, 2021 • Haramaya University. GPA 3.81
- MSc Degree in Computer Science• January 09, 2020 • Haramaya University. GPA 3.92
Relevant Courses: NLP, Big Data, Pervasive, Computer Vision and Image Processing, Design and Analysis of Algorithm, Distributed Systems, Embedded Systems, Research Methods
Thesis Title: Machine Learning Based Multi-Scale Sentiment Analysis for Afaan Oromo Posts
- BSc Degree in Computer Science• 2016-07-02• MEKELLE University. GPA 3.72
Relevant Courses: Linear Algebra, Probability and Statistics , Applied Mathematics I, Numerical Analysis ,OOP, Data Structures and Algorithms, Computer organization and architecture, OS, JAVA, Database, AI, Internet Programming I-II, and Compiler Design
Work Experience
- Web DEVELOPING • HARAMAYA UNIVERSITY • SEPTEMBER 2021– Present
Key responsibilities:
Integrated Student Information Management System development for Haramaya University
- Lecturer• Haramaya University • Department of Computer Science • September 2016/17– Present
Key responsibilities:
planning teaching, including lectures, seminars/tutorials and
learning materials
checking and assessing students' work
pursuing research
- Head, Department of Computer Science • HARAMAYA UNIVERSITY • August 2021– May 26, 2022
Key responsibilities:
Chairs 14 staff members, developed and opened new
program[MSc in Artificial Intelligence]
Planning and reporting
Recruit staff
- Head Registrar, College of Computing and Informatics • HARAMAYA UNIVERSITY • May 27, 2022-Present
Key responsibilities:
Communicating academic calendar of University
Managing student records and grades
Working on the graduation approval
- Adama Science and Technology | Sixth ETCPC Training Coordinator September 22-23, 2022
Projects
In this project, I took data using API provided by USGS_3DEP ( United States Geological Survey 3D Elevation Program). AgriTech is a company working on maize farms and this project is done for the study of maize farms for water flow across different geographical areas. Extraction, Visualization, and transformation of data were achieved in this project.
I apply machine learning techniques to the Wisconsin Diagnostic Breast Cancer (WDBC) data. The WDBC data is class labelled, hence it will be a classification problem. The data has two classes (B=Benign, M=Malignant) and 32 attributes, or features. In all testing I did using Causal inference and I saw that the "mean" features and low radius mean has a causal effect on the breast cancer diagnosis.
Using A/B testing to test if the ads that the advertising company ran resulted in a significant lift in brand awareness. Comparing machine learning models vs A/B testing gave me insights on what to use in which particular problem.
The purpose of this project is to build a data engineering pipeline that allows recording millions of Amharic speakers reading digital texts in-app and web platforms. For this project, the Amharic news text classification dataset with baseline performance dataset is used. The aim of this project is to produce a tool that can be deployed to process posting and receiving text and audio files from and into a data lake, apply transformation in a distributed manner, and load it into a warehouse in a suitable format to train a speech-to-text model.
Rossmann Pharmaceuticals is a pharmaceutical chain that has 1115 stores. Rossmann Pharmaceuticals’ finance team wants to forecast sales in all their 1115 stores across several cities six weeks ahead of time. Used different machine learning models like neural networks and random forest to build an end-to-end product that delivers this prediction to analysts in the finance team.
Before investing in a business it is a must to have the best understanding of the field. This project is all about analyzing TellCo's users and finding out whether it is worth buying or selling.
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